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Identifying significant edges via neighborhood information

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Listed:
  • Zhao, Na
  • Li, Jie
  • Wang, Jian
  • Li, Tong
  • Yu, Yong
  • Zhou, Tao

Abstract

The heterogeneous nature of real networks implies that different edges play different roles in network structure and functions, and thus to identify significant edges is of high value in both theoretical studies and practical applications. We propose the so-called second-order neighborhood (SN) index to quantify an edge’s significance in a network. We apply the edge percolation process to measure the significance of edges in maintaining the network connectivity. We compare the SN index with many other benchmark methods based on 15 real networks, showing that the proposed SN index outperforms other well-known methods.

Suggested Citation

  • Zhao, Na & Li, Jie & Wang, Jian & Li, Tong & Yu, Yong & Zhou, Tao, 2020. "Identifying significant edges via neighborhood information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    • Handle: RePEc:eee:phsmap:v:548:y:2020:i:c:s0378437119321533
    DOI: 10.1016/j.physa.2019.123877
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    References listed on IDEAS

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    Cited by:

    1. Mukashov, A., 2023. "Parameter uncertainty in policy planning models: Using portfolio management methods to choose optimal policies under world market volatility," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 187-202.

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